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Analysis of the Typology and Factors Affecting the Decline in Old Industrial Parks (노후산업단지의 쇠퇴 영향요인과 유형화에 관한 연구)

  • Park, Hwan Yong;Park, Ji Ho
    • Korea Real Estate Review
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    • v.27 no.4
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    • pp.7-20
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    • 2017
  • This study attempts to diagnose and categorize the characteristics of old industrial parks, and eventually link the results to the regeneration of industrial complexes. For this reason, we performed a factor analysis by utilizing 15 indices of 89 industrial parks, excluding 5 large equipment industry sites. The 15 indices were classified into 5 factors. Factor 1 can be described as a category of 'urbanization possibility' for the indices of building age, plot ratio of less than $1,650m^2$, and urbanization ratio of the surrounding area. Factor 2 can be described as a category of 'productive efficiency' for the indices of land productivity, amount of exports by land, employment productivity, and repair costs of industrial areas. Factor 3 can be described as a category of 'infrastructure amenity' for the indices of road ratio, plot ratio attached to the road, and parks and recreation ratio. Factor 4 can be described as a category of 'location potentiality' for the indices of land price, infrastructure age, and distance to the highway, while factor 5 can be described as a category of 'availability of supporting facilities' for the indices of parking lot ratio and supporting facility land ratio. By using these 5 factor scores, we were able to extract industrial parks included in the lower 25% of the factor score and searched for what kind of factor problem they have for each industrial park. Based on these results, this research will provide sufficient information on the decline of industrial parks with respect to their demerits. The results of this study show significant implications and contribute to the establishment of policies for regional competitiveness, as well as job creation, in the process of industrial regeneration.

Part-time Work in Sweden: The Coexistence in Tension of Flexibility and Gender Equality (스웨덴의 시간제근로: 유연성과 성평등의 긴장 속 공존)

  • Kim, Young-Mi
    • Korean Journal of Labor Studies
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    • v.17 no.1
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    • pp.297-323
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    • 2011
  • Part-time jobs in Sweden are highly feminized yet are in fair conditions in terms of job security, earnings, and collective representation. Three points are considered to be important to understand why part-time work in Sweden carries such positive characteristics. First, the part-time work in Sweden is widely spread not as a result of employers' need for labor flexibilization but as means to enhance the work-life balance, a value pursued within a broader social policy package to change the breadwinner model. Second, discrimination against part-time workers is restrained in Sweden because the boundary between part-time and full-time is not conspicuous. Most of part-time jobs are occupied by regular workers who exert the right to part-time work, hence may go back to the full-time status any time. Third, the regulation on overtime work of part-time workers as well as full-time workers is strong. It is largely agreed among researchers that part-time work contributed greatly to an increase of female employment rate in Sweden. Since the 1970s, the increased availability of part-time jobs induced married women who used to be economically inactive to the labor market and maintained them to be economically active throughout the child rearing period. From the gender perspective, one may still raise issues regarding part-time work in Sweden such as persistent feminization and strong occupational sex segregation. However, the observed trend shows that the part-time work in Sweden has functioned more as a stepping stone to the full-time work for women than as a women's trap.

A Integrated Model of Land/Transportation System

  • 이상용
    • Proceedings of the KOR-KST Conference
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    • 1995.12a
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    • pp.45-73
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    • 1995
  • The current paper presents a system dynamics model which can generate the land use anq transportation system performance simultaneously is proposed. The model system consists of 7 submodels (population, migration of population, household, job growth-employment-land availability, housing development, travel demand, and traffic congestion level), and each of them is designed based on the causality functions and feedback loop structure between a large number of physical, socio-economic, and policy variables. The important advantages of the system dynamics model are as follows. First, the model can address the complex interactions between land use and transportation system performance dynamically. Therefore, it can be an effective tool for evaluating the time-by-time effect of a policy over time horizons. Secondly, the system dynamics model is not relied on the assumption of equilibrium state of urban systems as in conventional models since it determines the state of model components directly through dynamic system simulation. Thirdly, the system dynamics model is very flexible in reflecting new features, such as a policy, a new phenomenon which has not existed in the past, a special event, or a useful concept from other methodology, since it consists of a lots of separated equations. In Chapter I, II, and III, overall approach and structure of the model system are discussed with causal-loop diagrams and major equations. In Chapter V _, the performance of the developed model is applied to the analysis of the impact of highway capacity expansion on land use for the area of Montgomery County, MD. The year-by-year impacts of highway capacity expansion on congestion level and land use are analyzed with some possible scenarios for the highway capacity expansion. This is a first comprehensive attempt to use dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions. The model structure is not very elaborate mainly due to the problem of the availability of behavioral data, but the model performance results indicate that the proposed approach can be a promising one in dealing comprehensively with complicated urban land use/transportation system.

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An Operations Study on a Home Health Nursing Demonstration Program for the Patients Discharged with Chronic Residual Health Care Problems (추후관리가 필요한 만성질환 퇴원환자 가정간호 시범사업 운영 연구)

  • 홍여신;이은옥;이소우;김매자;홍경자;서문자;이영자;박정호;송미순
    • Journal of Korean Academy of Nursing
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    • v.20 no.2
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    • pp.227-248
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    • 1990
  • The study was conceived in relation to a concern over the growing gap between the needs of chronic patients and the availability of care from the current health care system in Korea. Patients with agonizing chronic pain, discomfort, despair and disability are left with helplessly unprepared families with little help from the acute care oriented health care system after discharge from hospital. There is a great need for the development of an alternative means of quality care that is economically feasible and culturally adaptible to our society. Thus, the study was designed to demonstrate the effectiveness of home heath care as an alternative to bridge the existing gap between the patients' needs and the current practice of health care. The study specifically purports to test the effects of home care on health expenditure, readmission, job retention, compliance to health care regime, general conditions, complications, and self-care knowledge and practices. The study was guided by the operations research method advocated by the Primary Health Care Operations Research Institute(PRICOR) which constitutes 3 stages of research : namely, problem analysis solution development, and solution validation. The first step in the operations research was field preparation to develop the necessary consensus and cooperation. This was done through the formation of a consulting body at the hospital and a steering committee among the researchers. For the stage of problem analysis, the Annual Report of Seoul National University Hospital and the patients records for last 5 years were reviewed and selective patient interviews were conducted to find out the magnitude of chronic health problems and areas of unmect health care needs to finally decide on the kinds of health problems to study. On the basis of problem analysis, the solution development stage was devoted to home care program development asa solution alternative. Assessment tools, teaching guidelines and care protocols were developed and tested for their validity. The final stage was the stage of experimentation and evaluation. Patients with liver diseases, hemiplegic and diabetic conditions were selected as study samples. Discharge evaluation, follow up home care, measurement and evaluation were carried out according to the protocols of care and measurement plan for each patient for the period of 6 months after discharge. The study was carried out for the period from Jan. 1987 to Dec. 1989. The following are the results of the study presented according to the hypotheses set forth for the study ; 1. Total expenditures for the period of study were not reduced for the experimental group, however, since the cost per hospital visit is about 4 times as great as the cost per home visit, the effect of cost saving by home care will become a reality as home care replaces part of the hospital visits. 2. The effect on the rate of readmission and job retention was found to be statistically nonsignificant though the number of readmission was less among the experimental group receiving home care. 3. The effect on compliance to the health care regime was found to be statistically significant at the 5% level for hepatopathic and diabetic patients. 4. Education on diet, rest and excise, and medication through home care had an effect on improved liver function test scores, prevention of complications and self - care knowledge in hepatopathic patients at a statistically significant level. 5. In hemiplegic patient, home care had an effect on increased grasping power at a significant level. However. there was no significant difference between the experimental and control groups in the level of compliane, prevention of complications or in self-care practices. 6. In diabetic patients, there was no difference between the experimental and control groups in scores of laboratory tests, appearance of complications, and self-care knowledge or self -care practices. The above findings indicate that a home care program instituted for such short term as 6 months period could not totally demonstrate its effectiveness at a statistically significant level by quantitative analysis however, what was shown in part in this analysis, and in the continuous consultation sought by those who had been in the experimental group, is that home health care has a great potential in retarding or preventing pathological progress, facilitating rehabilitative and productive life, and improving quality of life by adding comfort, confidence and strength to patients and their families. For the further studies of this kind with chronic patients it is recommended that a sample of newly diagnosed patients be followed up for a longer period of time with more frequent observations to demonstrate a more dear- cut picture of the effectiveness of home care.

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A Framework on 3D Object-Based Construction Information Management System for Work Productivity Analysis for Reinforced Concrete Work (철근콘크리트 공사의 작업 생산성 분석을 위한 3차원 객체 활용 정보관리 시스템 구축방안)

  • Kim, Jun;Cha, Heesung
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.2
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    • pp.15-24
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    • 2018
  • Despite the recognition of the need for productivity information and its importance, the feedback of productivity information is not well-established in the construction industry. Effective use of productivity information is required to improve the reliability of construction planning. However, in many cases, on-site productivity information is hardly management effectively, but rather it relies on the experience and/or intuition of project participants. Based on the literature review and expert interviews, the authors recognized that one of the possible solutions is to develop a systematic approach in dealing with productivity information of the construction job-sites. It is required that the new system should not be burdensome to users, purpose-oriented information management, easy-to follow information structure, real-time information feedback, and productivity-related factor recognition. Based on the preliminary investigations, this study proposed a framework for a novel system that facilitate the effective management of construction productivity information. This system has utilized Sketchup software which has good user accessibility by minimizing additional data input and related workload. The proposed system has been designed to input, process, and output the pertinent information through a four-stage process: preparation, input, processing, and output. The inputted construction information is classified into Task Breakdown Structure (TBS) and Material Breakdown Structure (MBS), which are constructed by referring to the contents of the standard specification of building construction, and converted into productivity information. In addition, the converted information is also graphically visualized on the screen, allowing the users to use the productivity information from the job-site. The productivity information management system proposed in this study has been pilot-tested in terms of practical applicability and information availability in the real construction project. Very positive results have been obtained from the usability and the applicability of the system and benefits are expected from the validity test of the system. If the proposed system is used in the planning stage in the construction, the productivity information and the continuous information is accumulated, the expected effectiveness of this study would be conceivably further enhanced.

A Study on the Impact of Artificial Intelligence on Decision Making : Focusing on Human-AI Collaboration and Decision-Maker's Personality Trait (인공지능이 의사결정에 미치는 영향에 관한 연구 : 인간과 인공지능의 협업 및 의사결정자의 성격 특성을 중심으로)

  • Lee, JeongSeon;Suh, Bomil;Kwon, YoungOk
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.231-252
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    • 2021
  • Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.